ComfyUI Upscaler TensorRT
This project provides a Tensorrt implementation for fast image upscaling inside ComfyUI (3-4x faster)
Quick Technical Summary: ComfyUI Upscaler TensorRT
- Base VRAM Footprint:
- 3072 MB (8 GB Tier)
- Primary Dependencies:
- polygraphy, requests, tensorrt
- Min PyTorch / CUDA:
- PyTorch 2.0+ | CUDA 12.1+
- GitHub Repository:
- https://github.com/yuvraj108c/ComfyUI-Upscaler-Tensorrt
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does ComfyUI Upscaler TensorRT require?
Direct Answer: The ComfyUI node ComfyUI Upscaler TensorRT requires a minimum base VRAM of 3072MB and is optimized for GPUs with at least 8GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.
- Base VRAM:
- 3072MB (3.0GB)
- Recommended GPU:
- 8GB+ VRAM
- Low VRAM Mode:
- ✓ Supported
- Estimation Confidence:
- MEDIUM
Run ComfyUI Upscaler TensorRT locally
Honest estimate: this node typically needs ≥ 8GB VRAM in a real workflow (low-VRAM mode is supported).
Cheapest VRAM upgrade paths (live market prices)
- GeForce RTX 3060 12GB (Ultimate Budget VRAM King)Used: $209.62View eBay ↗
- GeForce RTX 4060 8GB (Modern Entry-Level)New: $303.50View Amazon ↗
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Interactive VRAM Compatibility Estimator
Your GPU has plenty of headroom. You can run this node safely with your active configurations!
Struggling with VRAM Crashes or Out-of-Memory Errors?
Running heavy models like FLUX or SDXL with ComfyUI Upscaler TensorRT? If you experience torch.cuda.OutOfMemoryError or driver timeouts, read our comprehensive troubleshooting guide to configure launch flags, enable tiled decoding, and avoid crashes.
Verify Compatibility for Your Specific GPU VRAM
Select your graphics card's VRAM capacity to view optimized batch sizes, suggested resolutions, and custom performance tips for ComfyUI Upscaler TensorRT:
What Python packages are required for ComfyUI Upscaler TensorRT?
Direct Answer: Running ComfyUI Upscaler TensorRT requires installing the following Python package dependencies: polygraphy, requests, tensorrt. Ensure your ComfyUI environment has these packages active before launching.
polygraphy
requests
tensorrtInteractive Setup & Dependency Resolver
# Loading command...Universal Architecture Compatibility
ComfyUI Upscaler TensorRT operates as a general-purpose processor without binding directly to a single checkpoint architecture. It can be paired across Stable Diffusion 1.5, SDXL, FLUX, and video diffusion pipelines.
Frequently Asked Questions
How much VRAM does ComfyUI Upscaler TensorRT require?
ComfyUI Upscaler TensorRT requires a minimum of 3072MB (3.0GB) of VRAM for base operation. For optimal performance, a GPU with at least 8GB of VRAM is recommended. This node supports low VRAM mode for resource-constrained setups.
Can I run ComfyUI Upscaler TensorRT on an RTX 3060, RTX 4070, or RTX 4090?
✅ RTX 3060 (12GB): Yes, fully compatible with 7.8GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 7.8GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 11.4GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 18.6GB headroom
How much VRAM does ComfyUI Upscaler TensorRT take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), ComfyUI Upscaler TensorRT runs smoothly on an RTX 3060 (12GB) with 7.8GB of headroom. This is sufficient to run the node alongside standard SD 1.5 and SDXL workflows in full precision. On an RTX 4090 (24GB VRAM), the node runs with extreme headroom on an RTX 4090 (24GB) with 18.6GB of dedicated headroom. This allows you to combine the node with massive models (like FLUX.1 Dev, Schnell, or Hunyuan Video) in full precision (FP16) without any offload flags.
What Python packages are required for ComfyUI Upscaler TensorRT?
To run ComfyUI Upscaler TensorRT, you need to install: polygraphy, requests, tensorrt. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running ComfyUI Upscaler TensorRT?
ComfyUI Upscaler TensorRT supports low VRAM mode. To reduce memory usage: (1) Enable --lowvram or --medvram flags in ComfyUI, (2) Reduce batch size to 1, (3) Use fp16 or fp8 precision if supported, (4) Close other GPU applications.
How do I install ComfyUI Upscaler TensorRT in ComfyUI?
To install ComfyUI Upscaler TensorRT: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/yuvraj108c/ComfyUI-Upscaler-Tensorrt, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.
Are you the author of this node?
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